Pronosticando el volumen del mercado interbancario de divisas: caso colombiano

En este trabajo se estudian las fortalezas y debilidades de los modelos de pronóstico del volumen de transacciones del mercado colombiano interbancario de divisas, generado por un modelo basado en árboles de decisión y dos tipos de redes neuronales, las Long short term memory y las temporal convolut...

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Fecha de publicación:
2023
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
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spa
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oai:repository.urosario.edu.co:10336/40984
Acceso en línea:
https://doi.org/10.48713/10336_40984
https://repository.urosario.edu.co/handle/10336/40984
Palabra clave:
Mercado FOREX
Análisis de series de tiempo
XGBOOST
Red LSTM
Red TCN
FOREX Market
Time series analysis
XGBOOST
LSTM network
TCN Network
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Attribution-NonCommercial-NoDerivatives 4.0 International
id EDOCUR2_4901b646951993d179b93b93d709e601
oai_identifier_str oai:repository.urosario.edu.co:10336/40984
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.none.fl_str_mv Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
dc.title.TranslatedTitle.none.fl_str_mv Forecasting the volume of the forex market: colombian case
title Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
spellingShingle Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
Mercado FOREX
Análisis de series de tiempo
XGBOOST
Red LSTM
Red TCN
FOREX Market
Time series analysis
XGBOOST
LSTM network
TCN Network
title_short Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
title_full Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
title_fullStr Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
title_full_unstemmed Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
title_sort Pronosticando el volumen del mercado interbancario de divisas: caso colombiano
dc.contributor.advisor.none.fl_str_mv Pérez Castañeda, Gabriel Camilo
dc.subject.none.fl_str_mv Mercado FOREX
Análisis de series de tiempo
XGBOOST
Red LSTM
Red TCN
topic Mercado FOREX
Análisis de series de tiempo
XGBOOST
Red LSTM
Red TCN
FOREX Market
Time series analysis
XGBOOST
LSTM network
TCN Network
dc.subject.keyword.none.fl_str_mv FOREX Market
Time series analysis
XGBOOST
LSTM network
TCN Network
description En este trabajo se estudian las fortalezas y debilidades de los modelos de pronóstico del volumen de transacciones del mercado colombiano interbancario de divisas, generado por un modelo basado en árboles de decisión y dos tipos de redes neuronales, las Long short term memory y las temporal convolutional nexworks, comparados con los modelos econométricos tradicionales para el estudio de series de tiempo.
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-09-15T21:02:26Z
dc.date.available.none.fl_str_mv 2023-09-15T21:02:26Z
dc.date.created.none.fl_str_mv 2023-08-25
dc.type.none.fl_str_mv bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.document.none.fl_str_mv Trabajo de grado
dc.type.spa.none.fl_str_mv Trabajo de grado
dc.identifier.doi.none.fl_str_mv https://doi.org/10.48713/10336_40984
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/40984
url https://doi.org/10.48713/10336_40984
https://repository.urosario.edu.co/handle/10336/40984
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.none.fl_str_mv Abierto (Texto Completo)
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
Abierto (Texto Completo)
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.none.fl_str_mv 51 pp
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad del Rosario
dc.publisher.department.spa.fl_str_mv Escuela de Ingeniería, Ciencia y Tecnología
dc.publisher.program.spa.fl_str_mv Maestría en Matemáticas Aplicadas y Ciencias de la Computación
institution Universidad del Rosario
dc.source.bibliographicCitation.none.fl_str_mv Montgomery, Douglas C; Jennings, Cheryl L; Kulahci, Murat (2008) Introduction to time series analysis and forecasting. En: Wiley series in probability and statistics. Hoboken, N.J: Wiley-Interscience; 9780471653974;
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spelling Pérez Castañeda, Gabriel Camilo896180cf-4061-48b3-8a01-28a37f5b6338-1Torres Medina, Paula AndreaMagíster en Matemáticas Aplicadas y Ciencias de la ComputaciónFull time63fd2b4d-5de5-415a-8ea7-dd1178f500d9-12023-09-15T21:02:26Z2023-09-15T21:02:26Z2023-08-25En este trabajo se estudian las fortalezas y debilidades de los modelos de pronóstico del volumen de transacciones del mercado colombiano interbancario de divisas, generado por un modelo basado en árboles de decisión y dos tipos de redes neuronales, las Long short term memory y las temporal convolutional nexworks, comparados con los modelos econométricos tradicionales para el estudio de series de tiempo.This paper studies the strengths and weaknesses of forecast models of the volume of transactions in the Colombian forex market. It analyzes a model based on decision trees and two types of neural networks, namely Long Short-Term Memory (LSTM) and Temporal Convolutional Networks (TCN), comparing them with traditional econometric models for the study of time series.51 ppapplication/pdfhttps://doi.org/10.48713/10336_40984 https://repository.urosario.edu.co/handle/10336/40984spaUniversidad del RosarioEscuela de Ingeniería, Ciencia y TecnologíaMaestría en Matemáticas Aplicadas y Ciencias de la ComputaciónAttribution-NonCommercial-NoDerivatives 4.0 InternationalAbierto (Texto Completo)http://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2Montgomery, Douglas C; Jennings, Cheryl L; Kulahci, Murat (2008) Introduction to time series analysis and forecasting. En: Wiley series in probability and statistics. Hoboken, N.J: Wiley-Interscience; 9780471653974;Hyndman, Rob J; Athanasopoulos, George (2021) Forecasting: Principles and Practice. Melbourne, Australia: OTexts;Bai, Shaojie; Kolter, J Zico; Koltun, Vladlen (2018) An Empirical Evaluation of Generic Convolutional and Recurrent Networks. : arXiv; Consultado en: 2023/6/10. Disponible en: http://arxiv.org/abs/1803.01271.Chen, Tianqi; Guestrin, Carlos (2016) XGBoost: A Scalable Tree Boosting System. En: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge. pp. 785-794 Consultado en: 2023/6/10. Disponible en: http://arxiv.org/abs/1603.02754; http://dx.doi.org/10.1145/2939672.2939785. Disponible en: 10.1145/2939672.2939785.McCulloch, W S; Pitts, W (1943) A logical calculus of the ideas immanent in nervous activity. En: Bulletin of Mathematical Biophysics 5. pp. 115–133 : Springer; Disponible en: http://dx.doi.org/10.1007/BF02478259. Disponible en: 10.1007/BF02478259.Rosenblatt, F (1958) The perceptron: A probabilistic model for information storage and. En: Psychological Review. 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Disponible en: https://www.bis.org/statistics/rpfx22_fx.htm.Murphy, John J (2000) Analisis Tecnico de Los Mercados Financieros (Spanish Edition). : Gestion 2000; 9788480884426;instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURMercado FOREXAnálisis de series de tiempoXGBOOSTRed LSTMRed TCNFOREX MarketTime series analysisXGBOOSTLSTM networkTCN NetworkPronosticando el volumen del mercado interbancario de divisas: caso colombianoForecasting the volume of the forex market: colombian casebachelorThesisTrabajo de gradoTrabajo de gradohttp://purl.org/coar/resource_type/c_7a1fEscuela de Ingeniería, Ciencia y TecnologíaORIGINALPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdfPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdfapplication/pdf1166817https://repository.urosario.edu.co/bitstreams/a98d4bcd-3dc9-4c10-b31c-dd127f9d06ea/downloadad837aa03f0796285e2f9b4dfb5ea688MD51Referencias.risReferencias.risapplication/x-research-info-systems35097https://repository.urosario.edu.co/bitstreams/76e5f833-4303-4ee1-8379-87fa71eba35e/download46c4d4d97a39118d25f50af91b6503b1MD54LICENSElicense.txtlicense.txttext/plain1483https://repository.urosario.edu.co/bitstreams/c2174506-2de3-4dce-8053-3ccc544afef3/downloadb2825df9f458e9d5d96ee8b7cd74fde6MD52CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8899https://repository.urosario.edu.co/bitstreams/12a1b595-5f2d-48c6-9a90-35980709c14b/download3b6ce8e9e36c89875e8cf39962fe8920MD55TEXTPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdf.txtPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdf.txtExtracted texttext/plain74902https://repository.urosario.edu.co/bitstreams/2df1e9a3-c8fb-40d0-9a74-f38de6dc9924/download2c5d1b8c5952cb290d89607d61b1914bMD56THUMBNAILPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdf.jpgPronosticando_el_volumen_del_mercado_interbancario_de_divisas_caso_colombiano.pdf.jpgGenerated Thumbnailimage/jpeg2824https://repository.urosario.edu.co/bitstreams/bd1388f0-d7dc-4ad2-a601-21793e6825b6/download26def30c93961876488e632b8df6e1c1MD5710336/40984oai:repository.urosario.edu.co:10336/409842024-08-23 09:10:09.631http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttps://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.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